Sharif Digital Repository

Nowadays, advanced and inexpensive pre-clinical methods for investigating the effects of anti-cancer drugs are expanding. One of the latest three-dimensional laboratory modeling for evaluating the effects of drugs is the use of tumor-on-chip technology, which actually models the physiological system of the body through three-dimensional scaffolds, multicellular cultures, and shaped vascular systems. In this study, three-dimensional culture of cancer cells was performed in the form of spheroids. A chip of U-shaped microstructures with and without gaps was used to trap cells and form cancer spheroids. We simulated the simultaneous effect of drug and oxygen concentration distribution inside the... 

Modeling and performance evaluation of the real time distributed systems is a significant problem. Stochastic activity network is one of the high level models used for this purpose. This network is an extension of generalized stochastic Petri net which is more powerful and flexible than other Petri net extensions. Checking the satisfiability of properties such as performance, dependability and user's expected properties is considerable in these models. Thus, using the approaches and generating modeling and model checking tools with the mentioned purpose is attractive. A model checker automatically checks the correctness of the system behaviors as properties against the model by getting the... 

This study has focused on the important problem of landing on a planet as an important current and future space mission. In this regard, dynamics modeling and integrated state estimation and control problems have been investigated in different views. To this aim, first a novel concurrent representation for translational and rotational kinematics has been developed based on the extension of modified Rodrigues parameters to dual space. This parameter set, called dual modified Rodrigues parameters (DMRP), is then utilized to establish an integrated roto-translational dynamic. The proposed DMRP-based kinematics and dynamics have been verified via comparison to traditional methods of... 

Prevalent deployment of Distributed Energy Resources(DERs) in the demand side of electrical energy grids has several advantages such as greenhouse gases emission reduction, mitigation of power losses in the distribution grids and abatement of the dependency on the wholesale generation companies. At the same time, it paves the way for the advent of local interactive energy trading frameworks. In the following thesis, a distributed data-driven algorithm is developed for market-clearing in a community-based local energy market. The social welfare maximization is considered as the objective of the energy trading. The production and demand of electricity are the decision variables of sellers and... 

Understanding biological systems requires extensive knowledge of individual parameters, and to study the processes of cell differentiation and cell behavior, a suitable environment must be created with the physiological conditions of the human body. For this purpose, with the knowledge of microfluidics, a microenvironment can be provided to study the behavior of cells on a small scale. The use of bone tissue model microfluidic chips is an alternative and new method in which it is possible to study the behavior of cells to differentiate into bone and to examine the toxicity of drugs, which in itself can help in the effective and successful treatment of these cases show. Therefore, in this... 

The main topic of this research is the navigation and control of a free-flying satellite with a robot manipulator while transferring and placing cargo on a space station. After connecting the cargo module, astronauts and robots need to deliver the available loads to the desired modules in a space station. Capturing an object or cargo is a critical issue studied extensively so far. However, delivery and placing of the cargo at the target point have not been investigated yet, to the best of the author’s knowledge; hence, this is a primary motivation for conducting the proposed research. After capturing the payload, the position and attitude of the manipulator with respect to the station’s... 

Cardiovascular disease (CVD) currently remains a considerable challenge for clinical treatments. CVDs account for N17.5 million deaths per year and will predictably increase to 23.6 million by 2030. The main purpose is to create human model systems to study the effect of disease mutations or drug treatment on the heart. In addition, engineered cardiac tissues are considered promising candidates to be transplanted to improve the function of diseased hearts. For engineered active tissues/organs, 3D bioprinting can fabricate complex tissue architecture with a spatiotemporal distribution of bioactive substances (cells, growth factors, and others) to better guide tissue regeneration. However,... 

Accurate and fast attitude estimation of a rigid body plays an essential role in the performance of a vehicle’s control system, especially aerospace vehicles. Ample works have been done to increase the accuracy and speed of the attitude estimation process, but all have been developed according to a model-based approach. This approach assumes that the torques acting on the body have a known dynamical model that is used for the attitude estimation. The purpose of the present research is to estimate the attitude via a model-free approach, i. e. dynamics of the torques acting on the body are no longer assumed to be known, and its learning is the next step. Thus, the problem formulation of this... 

This thesis presents a new approach to design structural output feedback controllers with stabilization and pole-placement at desired points on the S plane. It is assumed that the linear time-invariant system has no fixed mode corresponding to the specified control structure, outside the desired region of the closed-loop poles, such that the structural controller design problem is theoretically feasible. To this end, the structural output controller design problem is first transformed into a structurally equivalent problem based on the solution of a set of discrete linear programs. Then, by using the resultant structure, a new method is proposed for designing static and dynamic control loops... 

Cardiovascular diseases are among the leading causes of death worldwide. For instance, in 2015, almost 31% of the world’s mortality rate was due to these causes. One of these diseases is cardiac coronary vessels’ occlusion which leads to the insufficient blood supply to the heart tissue and cardiomyocytes death after Myocardial Infarction (MI). After MI, a hierarchy of events in the heart tissue changes heart muscle and forms cardiac fibrosis. This fibrotic tissue does not have the native one’s properties and function, so it will cause cardiac arrest and patient death. Therefore, it is obvious that vascular network plays a crucial role in the heart function. The importance of cardiac... 

This thesis addresses the problem of optimal distributed control of unknown interconnected systems. In order to deal with this problem, a data-driven learning framework for finding the optimal centralized and the suboptimal distributed controllers has been developed via convex optimization.First of all, the linear quadratic regulation (LQR) problem is formulated into a nonconvex optimization problem. Using Lagrangian duality theories, a semidefinite program is then developed that requires information about the system dynamics. It is shown that the optimal solution to this problem is independent of the initial conditions and represents the Q-function, an important concept in reinforcement... 

This thesis introduces a distributed backstepping control strategy based on reinforcement learning to achieve fixed-time consensus in high-order nonlinear multi-agent systems. Each agent, whether a leader or a follower, is modeled using a strict feedback approach, incorporating uncertainties as unknown nonlinear functions and disturbance signals across all state variables. The communication network among agents can be either directed or undirected, with a fixed topology. Each follower employs a control law derived from actor-critic networks, utilizing only the outputs from neighboring agents. The proposed method combines virtual and actual backstepping control laws, formulated from two key... 

Football transformation into an industry with extraordinary financial flow has made this popular sport an attractive field for sports analysts. The development of the computer science and data science has led to the emergence of a concept called football match analysis. The goalkeepers, as a unique member of football teams and regrading their unique features and characteristics, play a crucial role in the outcome of competitions and the success of the teams. Therefore, analysis of various aspects of their performance is one of the essential issues in the application of data science in football. In this research, three separate parts have been studied. In the first part, by using pre-match... 

This study investigates the motion planning problem for multiple agents with nonlinear dynamics in environments with static obstacles. Designing safe, smooth, and optimal trajectories for a group of agents operating concurrently in a shared space is a critical challenge in robotics, multi-agent systems, and autonomous navigation. Traditional methods often rely on initial guesses close to the optimal solution or become computationally inefficient at large scales. To address these challenges, this thesis proposes a novel computational framework based on the Alternating Direction Method of Multipliers (ADMM) and the Convex Feasible Set (CFS) algorithm. The framework decomposes the overall... 

Free-flying robots are critical for supporting human efforts during space missions. Recent advancements in multi-agent robotics, enabled by Multi-Agent Deep Reinforce- ment Learning (MADRL), have further enhanced the efficiency and autonomy of these systems. Multi-agent actor-critic methods with Centralized Training and Decentralized Execution (CTDE) enables robots for decentralized coordination in a continuous action space by addressing the problems of non-stationary and credit assignment in multi- agent environments. Notably, Multi-Agent Proximal Policy Optimization (MAPPO) has demonstrated superior performance compared to other methods in these environ- ments. Integrating the attention... 

In this study, the inventory allocation problem in the blood supply chain is investigated as a critical, perishable system characterized by a high level of uncertainty. The objective of this research is to develop an efficient decision-making framework for allocating red blood cells to hospitals within a weighted single-objective function that simultaneously considers minimizing shortages, minimizing blood wastage, prioritizing same-type blood fulfillment, and managing substitution costs by reducing the use of low-priority compatible substitutions. To this end, the problem was first formulated in a deterministic environment with a specified planning horizon and solved under four scenarios...